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COLT
1998
Springer
15 years 7 months ago
Learning One-Variable Pattern Languages in Linear Average Time
A new algorithm for learning one-variable pattern languages is proposed and analyzed with respect to its average-case behavior. We consider the total learning time that takes into...
Rüdiger Reischuk, Thomas Zeugmann
CORR
2006
Springer
130views Education» more  CORR 2006»
15 years 2 months ago
Genetic Programming for Kernel-based Learning with Co-evolving Subsets Selection
Abstract. Support Vector Machines (SVMs) are well-established Machine Learning (ML) algorithms. They rely on the fact that i) linear learning can be formalized as a well-posed opti...
Christian Gagné, Marc Schoenauer, Mich&egra...
ICML
1996
IEEE
16 years 3 months ago
Representing and Learning Quality-Improving Search Control Knowledge
Generating good, production-quality plans is an essential element in transforming planners from research tools into real-world applications, but one that has been frequently overl...
M. Alicia Pérez
ICML
2007
IEEE
16 years 3 months ago
Large-scale RLSC learning without agony
The advances in kernel-based learning necessitate the study on solving a large-scale non-sparse positive definite linear system. To provide a deterministic approach, recent resear...
Wenye Li, Kin-Hong Lee, Kwong-Sak Leung
PRL
2008
118views more  PRL 2008»
15 years 2 months ago
Bayes Machines for binary classification
In this work we propose an approach to binary classification based on an extension of Bayes Point Machines. Particularly, we take into account the whole set of hypotheses that are...
Daniel Hernández-Lobato, José Miguel...